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激光条纹自适应双向灰度重心提取算法。

Adaptive Bidirectional Gray-Scale Center of Gravity Extraction Algorithm of Laser Stripes.

机构信息

School of Mechanical Engineering, Taiyuan University of Science and Technology, Taiyuan 030024, China.

出版信息

Sensors (Basel). 2022 Dec 7;22(24):9567. doi: 10.3390/s22249567.

Abstract

Aiming at the realization of fast and high-precision detection of the workpiece, an adaptive bidirectional gray-scale center of gravity extraction algorithm for laser stripes is proposed in this paper. The algorithm is processed in the following steps. Firstly, the initial image processing area is set according to the floating field of the camera's light stripe, followed by setting the adaptive image processing area according to the actual position of the light stripe. Secondly, the center of light stripe is obtained by using the method of combining the upper contour with the barycenter of the bidirectional gray-scale. The obtained center of the light stripe is optimized by reducing the deviation from adjacent center points. Finally, the slope and intercept are used to complete the breakpoint. The experimental results show that the algorithm has the advantages of high speed and precision and has specific adaptability to the laser stripes of the complex environment. Compared with other conventional algorithms, it greatly improves and can be used in industrial detection.

摘要

针对工件的快速、高精度检测的实现,本文提出了一种激光条纹自适应双向灰度重心提取算法。该算法的处理步骤如下:首先,根据相机光条纹的浮动场设置初始图像处理区域,然后根据光条纹的实际位置设置自适应图像处理区域。其次,采用上下轮廓与双向灰度重心相结合的方法获取光条纹中心,通过减少与相邻中心点的偏差来优化获得的光条纹中心。最后,利用斜率和截距完成断点。实验结果表明,该算法具有速度快、精度高的优点,对复杂环境下的激光条纹具有特定的适应性。与其他常规算法相比,它有了很大的改进,可以应用于工业检测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/156e/9784518/a7a9827ba8f8/sensors-22-09567-g001.jpg

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